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> These models are just clever image uncompression. Nothing scary here. :) Yes and no. The latent representation space can be seen as a kind of result of compr
by manux 11y ago
> These models are just clever image uncompression. Nothing scary here. :)
Yes and no. The latent representation space can be seen as a kind of result of compression, but the opposite is going on. As you say, these models generate images from (latent space) random noise, but there's no direct mapping from image space to latent space (as there are with autoencoders), so no way to compress, really.
- murbard2 11y agoOf course there is: direct enumeration. If you insist on a practical way to do it, gradient descent on the latent vector would probably work well given the type of results DeepDream has obtained.
- gcr 11y agoI think variational autoencoders (which explicitly model the compression step and the decompression step) seem like the more classical way to do it.